CAREER: Characterizing Climate Change Feedbacks in Arctic Ponds while Incorporating Next-Generation Technologies and Arctic Field Experiences in Education
CAREER: Characterizing Climate Change Feedbacks in Arctic Ponds while Incorporating Next-Generation Technologies and Arctic Field Experiences in Education
批准号:
2239038
负责人:
Christian Andresen
金额:
$70.42万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-06-01 至 2028-05-31
中文摘要
湿地是北极地貌的重要组成部分,以其众多的多边形融化池塘为特点。这些北极池塘栖息地是生物多样性和碳循环的热点。特别是,池塘是甲烷(CH4)的主要排放者,甲烷是一种会加剧气候变化的强有力的温室气体。该项目将描述北极湿地池塘在区域陆地-大气碳交换中的作用,估计它们对大气的甲烷贡献,并评估它们在过去50年中的变化,以更好地预测它们未来在北极碳循环和对气候的反馈中的作用。该项目还有两个主要的教育组成部分:(1)培训来自代表性不足群体的下一代科学家,以设计和领导旨在加深对北极系统的了解的北极实地考察工作;(2)将虚拟现实、无人机传感器和机器学习纳入教育,以提高对科学、技术、经济、社会和环境科学及极地科学的参与度。这些学生与技术的互动将激发创造力和创新,为他们提供学术和行业职位的竞争优势。该项目的更广泛影响包括与阿拉斯加土著社区的夏季外联活动,以及学生设计的一本图册,通过制图的角度描绘北极景观、土著社区和气候变化的威胁。这本书将向普通读者传达和提高对北极地区的认识。尽管池塘对区域CH4预算很重要,但总体上对池塘的研究不足,因此,在北极和全球CH4估计和地球系统模型中,池塘的比例较低。因此,它们的演变将如何影响未来的陆地-大气碳交换和对气候的潜在反馈尚不清楚。这项研究将(1)建立对多边形池塘表层大气碳动态的基础性认识,(2)表征CH4排放的时间和途径,(3)揭示气候变化下池塘的演变及其碳影响。使用尖端技术,包括涡旋协方差通量系统、无人机和航空成像光谱仪、无人机激光雷达和深度学习人工智能,将使我们能够表征北极池塘自下而上和自上而下的区域尺度CH4排放。此外,这项研究将挽救历史记录,以更好地了解过去50年来池塘的生物地球化学变化,以回答这些水生系统的演变在哪里、何时以及如何影响了表层大气对气候的碳反馈。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Wetlands represent a significant portion of the Arctic landscape and are characterized by their numerous polygonal thaw ponds. These Arctic pond habitats are hotspots for biodiversity and carbon cycling. Particularly, ponds are key emitters of methane (CH4), a potent greenhouse gas that enhances climate change. This project will characterize the role of Arctic wetland ponds in regional land-atmosphere carbon exchange, estimate their contributions of CH4 to the atmosphere, and assess how they have changed over the past 50 years to better anticipate their future role in Arctic carbon cycling and feedbacks to climate. This project also has two major educational components: (1) train the next generation of scientists from underrepresented groups to design and lead Arctic fieldwork intended to deepen understanding of the Arctic system and (2) incorporate virtual reality, drone sensors, and machine learning into education to improve engagement in STEM and Polar Sciences. These student-technology interactions will spur creativity and innovation, providing them with a competitive edge for academic and industry positions. The broader impacts of the project include summer outreach activities with Alaskan Indigenous communities and a photo book design by students that portrays Arctic landscapes, Indigenous communities, and the threats of climate change through a cartographic perspective. The book will communicate and promote awareness about the Arctic region to a general audience.Despite their importance to regional CH4 budgets, ponds have been generally understudied and thus, underrepresented in Arctic and global CH4 estimates and earth system models. Therefore, it is unknown how their evolution will impact future land-atmosphere carbon exchange and potential feedbacks to climate. This study will (1) establish a foundational understanding of surface-atmosphere carbon dynamics of polygonal ponds, (2) characterize the timing and pathways of CH4 emissions, and (3) unravel the evolution of ponds under climate change and its carbon implications. The use of cutting-edge technologies including eddy-covariance flux system, drone & airborne imaging spectroscopy, drone LIDAR, and deep-learning Artificial Intelligence will allow us to characterize bottom-up and top-down regional scale CH4 emissions from arctic ponds. In addition, this study will rescue historical records to better understand biogeochemical changes of ponds over the past 50 years to answer where, when, and how the evolution of these aquatic systems has influenced surface-atmosphere carbon feedbacks to climate.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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会议论文
Collaborative Research: Predicting Micro to Macro-scale Hot-spot and Hot-moment dynamics in Arctic Tundra Ecosystems
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批准号:2311075
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项目类别:Continuing Grant
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资助金额:$30.3万
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财政年份:2023
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负责人:Christian Andresen
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依托单位:
海外基金